Validation of an algorithm to estimate gestational age in electronic health plan databases

Antenatal care inequalities in South Korea: An analysis of health insurance claims data (2013-2022) in a high-resource, high-use country

OBJECTIVE

The aim of the present study was to explore inequalities in antenatal care (ANC) in South Korea. Based on the guidelines of the WHO, we categorized less than eight visits to an obstetrical facility as insufficient ANC. We examined ANC inequalities associated with age, disability, nationality, income, and geographic accessibility.

METHODS

We extracted delivery event claimed from 2013 to 2022 from the National Health Insurance Service database. By tracing back 270 days from the delivery date, we counted the number of antenatal visits for each childbirth and calculated the proportion of women with insufficient ANC and assessed both absolute and relative inequalities for each population group. The logistic regression analysis for both underuse and overuse of ANC were conducted.

RESULTS

Out of 3 416 517 childbirths, 104 109 women (3.0%) had fewer than eight ANC visits. Although the average number of ANC visits reached 18.7 in 2022, significant inequalities persisted across different population groups. The insufficient ANC rate was 28.1% for teenage women, 6.4% for disabled women, 10.7% for non-Korean women, and 15.2% for dependents of medical aid households. Women with low income and those living in obstetric care underserved areas also exhibited higher ANC insufficiency. From 2021 to 2022, sufficiency in ANC decreased for teenage, disabled, and non-Korean women, highlighting the effects of the COVID-19 pandemic.

CONCLUSION

Antenatal care inequalities are evident in South Korea's well-resourced health system. There is a need for further investigation into these disparities and the qualitative aspects of maternity care services.

Use of the Sentinel System to Examine Medical Product Use and Outcomes During Pregnancy

While many pregnant individuals use prescription medications, evidence supporting product safety during pregnancy is often inadequate. Existing electronic healthcare data sources provide large, diverse samples of health plan members to allow for the study of medical product utilization during pregnancy, as well as pregnancy, maternal, and infant outcomes. The Sentinel System is a national medical product surveillance system that includes administrative claims and electronic health record databases from large national and regional health insurers. In addition to these data sources, Sentinel develops and maintains a sizeable selection of analytic tools to facilitate epidemiologic analyses in a way that protects patient privacy and health system autonomy. In this article, we provide an overview of Sentinel System infrastructure, including the Mother-Infant Linkage Table, parameterizable analytic tools, and algorithms to estimate gestational age and identify pregnancy outcomes. We also describe past and future Sentinel work that contributes to our understanding of the way medical products are used and the safety of these products during pregnancy.

Timing of treatment for opioid use disorder among birthing people

BACKGROUND

The number of pregnant women with opioid use disorder (OUD) has increased over time. Although effective treatment options exist, little is known about the extent to which women receive treatment during pregnancy and at what stage of pregnancy care is initiated.

METHODS

Using a national private health insurance claims database, we identified women aged 13-49 who gave birth in 2006-2019 and had an OUD or nonfatal opioid overdose (NFOO) diagnosis during the year prior to or at delivery. We then identified women who received their first OUD treatment prior to or during pregnancy. In this cross-sectional study, we investigated how rates and timing of the initial OUD treatment changed over time. Furthermore, we examined factors associated with early initiation of OUD treatment among birthing people.

RESULTS

Of the 7057 deliveries from 6747 women with OUD or NFOO, 63.3 % received any OUD treatment. Rates of OUD treatment increased from 42.9 % in 2006 to 69 % in 2019. Of those treated, in 2006, 54.5 % received their first treatment prior to conception and 24.2 % initiated care during the 1st trimester. In 2019, 68.9 % received their first treatment prior to conception, and 15.1 % initiated care during the 1st trimester. The percentage of women who were first treated in the 2nd trimester or later decreased from 21.2 % in 2006 to 16.1 % in 2019. Factors associated with early treatment initiation include being 25 years or older (age 25-34: aOR, 1.51, 95 % CI, 1.28-1.78; age 35-49: aOR, 1.82, 95 % CI, 1.39-2.37), living in urban areas (aOR, 1.28; 95 % CI, 1.05-1.56), having pre-existing behavioral health comorbidities such as anxiety disorders (aOR, 1.8; 95 % CI, 1.40-2.32), mood disorders (aOR, 1.63; 95 % CI, 1.02-2.61), and substance use disorder other than OUD (aOR, 2.56; 95 % CI, 2.03-3.32).

CONCLUSION

Overall, rates of OUD treatment increased over time, and more women initiated OUD treatment prior to conception. Despite these improvements, over one-third of pregnant women with OUD/NFOO either received no treatment or did not initiate care until the 3rd trimester in 2019. Future research should examine barriers to OUD treatment initiation among pregnant women.

Persistent Bacterial Vaginosis and Risk for Spontaneous Preterm Birth

OBJECTIVE

The aim of this study was to determine the association between persistent bacterial vaginosis (BV) in pregnancy and risk for spontaneous preterm birth (sPTB).

STUDY DESIGN

Retrospective data from IBM MarketScan Commercial Database were analyzed. Women aged between 12 and 55 years with singleton gestations were included and linked to an outpatient medications database and medications prescribed during the pregnancy were analyzed. BV in pregnancy was determined based on both a diagnosis of BV and treatment with metronidazole and/or clindamycin, and persistent treatment of BV was defined as BV in more than one trimester or BV requiring more than one antibiotic prescription. Odds ratios were calculated comparing sPTB frequencies in those with BV, or persistent BV, to women without BV in pregnancy. Survival analysis using Kaplan-Meier curves for the gestational age at delivery was also performed.

RESULTS

Among a cohort of 2,538,606 women, 216,611 had an associated International Classification of Diseases, 9th Revision or 10th Revision code for diagnosis of BV alone, and 63,817 had both a diagnosis of BV and were treated with metronidazole and/or clindamycin. Overall, the frequency of sPTB among women treated with BV was 7.5% compared with 5.7% for women without BV who did not receive antibiotics. Relative to those without BV in pregnancy, odds ratios for sPTB were highest in those treated for BV in both the first and second trimester (1.66 [95% confidence interval [CI]: 1.52, 1.81]) or those with three or more prescriptions in pregnancy (1.48 [95% CI: 1.35, 1.63].

CONCLUSION

Persistent BV may have a higher risk for sPTB than a single episode of BV in pregnancy.

KEY POINTS

· Persistent BV beyond one trimester may increase the risk for sPTB.. · Persistent BV requiring more than one prescription may increase the risk for sPTB.. · Almost half of antibiotic prescriptions treating BV in pregnancy are filled after 20 weeks gestation..

Epidemiology of Medically Attended Respiratory Syncytial Virus Lower Respiratory Tract Infection in Japanese Children, 2011-2017

BACKGROUND

The objective was to report critical respiratory syncytial virus (RSV)-related epidemiological and healthcare resource utilization measures among Japanese children stratified by gestational and chronological age groups.

METHODS

The JMDC (formerly the Japan Medical Data Center) was used to retrospectively identify infants with or without RSV infection (beginning between 1 February 2011 and 31 January 2016, with follow-up through 31 December 2017). The incidence of RSV medically attended lower respiratory tract infection (MALRI) was captured by flagging hospitalizations, outpatient, and emergency department/urgent care visits with an RSV diagnosis code during the season.

RESULTS

Of 113 529 infants and children identified, 17 022 (15%) had an RSV MALRI (14 590 during the season). The RSV MALRI and hospitalization rates in the first 5 months were 14.3/100 child-years (CY) and 6.0/100 CY, respectively (13.4/100 and 5.8/100 CY for full-term infants and 20/100 and 6.8/100 CY for late preterm infants, respectively). Among those with ≥1 type of MALRI event during the RSV season, >80% of children had it by 24 months of chronological age, although this observation differed by prematurity status. Sixty percent of healthcare resource utilization measures started in the outpatient setting.

CONCLUSIONS

This study emphasizes the RSV burden in young children and critically highlights the data needed to make decisions about new preventive strategies.

Acute health care utilization in the first 24 months postpartum by rurality and pregnancy complications: A prospective cohort study

OBJECTIVE

To estimate the rate of acute health care use (hospitalizations and emergency department [ED] visits) among postpartum persons by rurality of residence and pregnancy complications.

DATA SOURCES AND STUDY SETTING

2006-2021 data from the Maine Health Data Organization's All Payer Claims Data.

STUDY DESIGN

We estimated the rates of hospitalizations and ED visits during the first 24 months postpartum, separately, overall and by four-level rurality of residence (urban, large rural, small rural, and isolated rural) and by pregnancy complications (prenatal depression, hypertensive disorders of pregnancy [HDP], and gestational diabetes mellitus [GDM]). We used Poisson regression models, adjusting for potential confounders. Data were weighted to account for censoring before 24 months postpartum.

DATA EXTRACTION METHODS

Deliveries during 2007-2019 (n = 122,412).

PRINCIPAL FINDINGS

Approximately 4% of persons had at least one hospitalization within 24 months postpartum (mean monthly rate per 100 deliveries = 0.35). Adjusted rates were not different by rurality. Persons with prenatal depression (adjusted rate ratio [aRR] = 1.9; 95% confidence interval [CI] 1.5-2.5), HDP (aRR = 1.4; 1.0-2.0), and GDM (aRR = 1.4; 0.9-2.0) had higher hospitalization rates than those without these conditions. Approximately 44% of persons had at least one ED visit within 24 months postpartum (mean monthly rate per 100 deliveries = 5.4). Adjusted ED rates were higher for persons living in small rural areas as compared with urban areas (aRR = 1.3; 1.2-1.4). Persons with prenatal depression (aRR = 1.8; 1.7-1.9), HDP (aRR = 1.1; 1.0-1.2), and GDM (aRR = 1.3; 1.2-1.4) had higher ED rates than those without these conditions; ED rates were highest among those living in small rural areas.

CONCLUSION

New policies and care practices may be needed to prevent acute health care encounters in the first 24 months after delivery for persons with common pregnancy conditions. Efforts to identify why postpartum people living in small rural areas have higher rates of ED visits are warranted.

Accounting for Twins and Other Multiple Births in Perinatal Studies Conducted Using Healthcare Administration Data

The analysis of perinatal studies is complicated by twins and other multiple births even when they are not the exposure, outcome, or a confounder of interest. Common approaches to handling multiples in studies of infant outcomes include restriction to singletons, counting outcomes at the pregnancy-level (i.e., by counting if at least one twin experienced a binary outcome), or infant-level analysis including all infants and, typically, accounting for clustering of outcomes by using generalised estimating equations or mixed effects models. Several healthcare administration databases only support restriction to singletons or pregnancy-level approaches. For example, in MarketScan insurance claims data, diagnoses in twins are often assigned to a single infant identifier, thereby preventing ascertainment of infant-level outcomes among multiples. Different approaches correspond to different causal questions, produce different estimands, and often rely on different assumptions. We demonstrate the differences that can arise from these different approaches using Monte Carlo simulations, algebraic formulas, and an applied example. Furthermore, we provide guidance on the handling of multiples in perinatal studies when using healthcare administration data.

Postpartum Depression in Reproductive-Age Women With and Without Rheumatic Disease: A Population-Based Matched Cohort Study

OBJECTIVE

To examine postpartum depression (PPD) among women with axial spondyloarthritis (axSpA), psoriatic arthritis (PsA), or rheumatoid arthritis (RA) in comparison with a matched population without rheumatic disease (RD).

METHODS

A retrospective analysis using the 2013-2018 IBM MarketScan Commercial Claims and Encounters Database was conducted. Pregnant women with axSpA, PsA, or RA were identified, and the delivery date was used as the index date. We restricted the sample to women ≤ 55 years with continuous enrollment ≥ 6 months before date of last menstrual period and throughout pregnancy. Each patient was matched with 4 individuals without RD on: (1) maternal age at delivery, (2) prior history of depression, and (3) duration of depression before delivery. Cox frailty proportional hazards models estimated the crude and adjusted hazard ratios (aHR) and 95% CI of incident postpartum depression within 1 year among women with axSpA, PsA, or RA (axSpA/PsA/RA cohort) compared to the matched non-RD comparison group.

RESULTS

Overall, 2667 women with axSpA, PsA, or RA and 10,668 patients without any RD were included. The median follow-up time in days was 256 (IQR 93-366) and 265 (IQR 99-366) for the axSpA/PsA/RA cohort and matched non-RD comparison group, respectively. Development of PPD was more common in the axSpA/PsA/RA cohort relative to the matched non-RD comparison group (axSpA/PsA/RA cohort: 17.2%; matched non-RD comparison group: 12.8%; aHR 1.22, 95% CI 1.09-1.36).

CONCLUSION

Postpartum depression is significantly higher in women of reproductive age with axSpA/PsA/RA when compared to those without RD.

Who is pregnant? Defining real-world data-based pregnancy episodes in the National COVID Cohort Collaborative (N3C)

Objectives

To define pregnancy episodes and estimate gestational age within electronic health record (EHR) data from the National COVID Cohort Collaborative (N3C).

Materials and Methods

We developed a comprehensive approach, named Hierarchy and rule-based pregnancy episode Inference integrated with Pregnancy Progression Signatures (HIPPS), and applied it to EHR data in the N3C (January 1, 2018-April 7, 2022). HIPPS combines: (1) an extension of a previously published pregnancy episode algorithm, (2) a novel algorithm to detect gestational age-specific signatures of a progressing pregnancy for further episode support, and (3) pregnancy start date inference. Clinicians performed validation of HIPPS on a subset of episodes. We then generated pregnancy cohorts based on gestational age precision and pregnancy outcomes for assessment of accuracy and comparison of COVID-19 and other characteristics.

Results

We identified 628 165 pregnant persons with 816 471 pregnancy episodes, of which 52.3% were live births, 24.4% were other outcomes (stillbirth, ectopic pregnancy, abortions), and 23.3% had unknown outcomes. Clinician validation agreed 98.8% with HIPPS-identified episodes. We were able to estimate start dates within 1 week of precision for 475 433 (58.2%) episodes. 62 540 (7.7%) episodes had incident COVID-19 during pregnancy.

Discussion

HIPPS provides measures of support for pregnancy-related variables such as gestational age and pregnancy outcomes based on N3C data. Gestational age precision allows researchers to find time to events with reasonable confidence.

Conclusion

We have developed a novel and robust approach for inferring pregnancy episodes and gestational age that addresses data inconsistency and missingness in EHR data.

Distribution of gestational age at birth by maternal and infant characteristics in U.S. birth certificate data: Informing gestational age assumptions when clinical estimates are not available

PURPOSE

We aimed to describe the distribution of gestational age at birth (GAB) to inform the estimation of GAB when clinical or obstetric estimates are not available for perinatal pharmacoepidemiology studies.

METHODS

We estimated GAB (median, mode, mean, and standard deviation) and percentage born at each gestational week in groups based on plurality and other variables for live births in CDC's U.S. birth data.

RESULTS

In 2020, 3 617 213 newborns had birth certificates with nonmissing GAB. Among singletons (3 501 693), median and mode GAB were both 39 weeks. Births with lower median GAB were from women with eclampsia (37 weeks) or receiving intensive care (37 weeks); newborns receiving intensive care (37 weeks); newborns with birth weight <2500 g (35 weeks), <1500 g (28 weeks), or <1000 g (25 weeks); and newborns not discharged alive (23 weeks). Among twins (112 633), median GAB was 36 weeks (mode, 37 weeks). Additional noteworthy groups were women with 0-6 prenatal visits (median, 34 weeks) or 7-8 prenatal visits (median, 35 weeks) or aged 15-19 years (median, 35 weeks).

CONCLUSIONS

Some maternal and infant groups had distinct GAB distributions in the United States. This information can be useful in estimating GAB when individual-level clinical estimates are not available, such as in database studies of medication use during pregnancy.

Mental Health Within 24 Months After Delivery Among Women with Common Pregnancy Conditions

Objective: The aim of this study is to estimate the risk of a new mental health diagnosis within the first 24 months postpartum among women with common pregnancy conditions, overall and by rurality. Materials and Methods: This longitudinal population-based study used the Maine Health Data Organization's All-Payer Claims Data to estimate the cumulative risk of a new mental health disorder diagnosis in the first 24 months postpartum among women with deliveries during 2007-2019 and who did not have a mental health diagnosis before pregnancy. Cox models were used to estimate hazard ratios for common pregnancy conditions (prenatal depression, gestational diabetes [GDM], and hypertensive disorders of pregnancy [HDP]) on the new diagnosis of five mental health conditions, separately. Models were adjusted for maternal demographics and pregnancy characteristics. Results: Of the 123,125 deliveries, the cumulative risk of being diagnosed in the first 24 months postpartum with depression was 28%, anxiety 25%, bipolar disorder 3%, post-traumatic stress disorder 6%, and schizophrenia/psychotic disorder 1%. Women with prenatal depression were at higher risk of having a postpartum mental health diagnosis compared with women without prenatal depression (adjusted hazard ratios [aHRs] ranged from 2.5 [for anxiety] to 4.1 [for postpartum depression]). Risk of having postpartum depression was modestly higher among women with HDP, as was the risk of postpartum bipolar disorder among those with GDM. Findings were generally similar between women living in rural versus urban areas. Conclusions: Effective interventions to prevent, screen, and treat mental health conditions among women with pregnancy complications for an extended time postpartum are warranted.

Wildfire smoke exposure and early childhood respiratory health: a study of prescription claims data

Wildfire smoke is associated with short-term respiratory outcomes including asthma exacerbation in children. As investigations into developmental wildfire smoke exposure on children's longer-term respiratory health are sparse, we investigated associations between developmental wildfire smoke exposure and first use of respiratory medications. Prescription claims from IBM MarketScan Commercial Claims and Encounters database were linked with wildfire smoke plume data from NASA satellites based on Metropolitan Statistical Area (MSA). A retrospective cohort of live infants (2010-2016) born into MSAs in six western states (U.S.A.), having prescription insurance, and whose birthdate was estimable from claims data was constructed (N = 184,703); of these, gestational age was estimated for 113,154 infants. The residential MSA, gestational age, and birthdate were used to estimate average weekly smoke exposure days (smoke-day) for each developmental period: three trimesters, and two sequential 12-week periods post-birth. Medications treating respiratory tract inflammation were classified using active ingredient and mode of administration into three categories:: 'upper respiratory', 'lower respiratory', 'systemic anti-inflammatory'. To evaluate associations between wildfire smoke exposure and medication usage, Cox models associating smoke-days with first observed prescription of each medication category were adjusted for infant sex, birth-season, and birthyear with a random intercept for MSA. Smoke exposure during postnatal periods was associated with earlier first use of upper respiratory medications (1-12 weeks: hazard ratio (HR) = 1.094 per 1-day increase in average weekly smoke-day, 95%CI: (1.005,1.191); 13-24 weeks: HR = 1.108, 95%CI: (1.016,1.209)). Protective associations were observed during gestational windows for both lower respiratory and systemic anti-inflammatory medications; it is possible that these associations may be a consequence of live-birth bias. These findings suggest wildfire smoke exposure during early postnatal developmental periods impact subsequent early life respiratory health.

Maternal comorbidity and adverse perinatal outcomes in survivors of adolescent and young adult cancer: A cohort study

OBJECTIVE

To evaluate risks of preterm birth (PTB) and severe maternal morbidity (SMM) in female survivors of adolescent and young adult cancer and assess maternal comorbidity as a potential mechanism. To determine whether associations differ by use of assisted reproductive technology (ART).

DESIGN

Retrospective cohort.

SETTING

Commercially insured females in the USA.

SAMPLE

Females with live births from 2000-2019 within a de-identified US administrative health claims data set.

METHODS

Log-binomial regression models estimated relative risks of PTB and SMM by cancer status and tested for effect modification. Causal mediation analysis evaluated the proportions explained by maternal comorbidity.

MAIN OUTCOME MEASURES

PTB and SMM.

RESULTS

Among 46 064 cancer survivors, 2440 singleton births, 214 multiple births and 2590 linked newborns occurred after cancer diagnosis. In singleton births, the incidence of PTB was 14.8% in cancer survivors versus 12.4% in females without cancer (aRR 1.19, 95% CI 1.06-1.34); the incidence of SMM was 3.9% in cancer survivors versus 2.4% in females without cancer (aRR 1.44, 95% CI 1.13-1.83). Cancer survivors had more maternal comorbidities before and during pregnancy; 26% of the association between cancer and PTB and 30% of the association between cancer and SMM was mediated by maternal comorbidities. Tests for effect modification of cancer status on perinatal outcomes by ART were non-significant.

CONCLUSIONS

Preterm birth and SMM risks were modestly increased after cancer. Significant proportions of elevated risks may result from increased comorbidities. ART did not significantly modify the association between adolescent and young adult cancer and adverse perinatal outcomes. The prevention and treatment of comorbidities provides an opportunity to improve perinatal outcomes among cancer survivors.

Validation of an ICD-9-Based Algorithm to Identify Stillbirth Episodes from Medicaid Claims Data

INTRODUCTION

In administrative data, accurate timing of exposure relative to gestation is critical for determining the effect of potential teratogen exposure on pregnancy outcomes.

OBJECTIVE

To develop an algorithm for identifying stillbirth episodes in the ICD-9-CM era using national Medicaid claims data (1999-2014).

METHODS

Unique stillbirth episodes were identified from clusters of medical claims using a hierarchy that identified the encounter with the highest potential of including the actual stillbirth delivery and that delineated subsequent pregnancy episodes. Each episode was validated using clinical detail on retrieved medical records as the gold standard.

RESULTS

Among 220 retrieved records, 197 were usable for validation of 1417 stillbirth episodes identified by the algorithm. The positive predictive value (PPV) was 64.0% (57.3-70.7%) overall, 80.4% (73.8-87.1%) for inpatient episodes, 28.2% (14.1-42.3%) for outpatient-only episodes, and 20.0% (2.5-37.5%) for outpatient episodes with overlapping hospitalizations. The absolute difference between the dates of the algorithm-specified stillbirth delivery and the medical record-based event was 4.2 ± 24.3 days overall, 1.7 ± 7.7 days for inpatient episodes, 14.3 ± 51.4 days for outpatient-only episodes, and 1.0 ± 2.0 days for outpatient episodes that overlapped with a hospitalization. Excluding all outpatient episodes, as well as pregnancies involving multiple births, the PPV increased to 82.7% (76.8-89.8%).

CONCLUSIONS

Our algorithm to identify stillbirths from administrative claims data had a moderately high PPV. Positive predictive value was substantially increased by restricting the setting to inpatient episodes and using only input diagnostic codes for singleton stillbirths.

Reproducible variability: assessing investigator discordance across 9 research teams attempting to reproduce the same observational study

OBJECTIVE

Observational studies can impact patient care but must be robust and reproducible. Nonreproducibility is primarily caused by unclear reporting of design choices and analytic procedures. This study aimed to: (1) assess how the study logic described in an observational study could be interpreted by independent researchers and (2) quantify the impact of interpretations' variability on patient characteristics.

MATERIALS AND METHODS

Nine teams of highly qualified researchers reproduced a cohort from a study by Albogami et al. The teams were provided the clinical codes and access to the tools to create cohort definitions such that the only variable part was their logic choices. We executed teams' cohort definitions against the database and compared the number of subjects, patient overlap, and patient characteristics.

RESULTS

On average, the teams' interpretations fully aligned with the master implementation in 4 out of 10 inclusion criteria with at least 4 deviations per team. Cohorts' size varied from one-third of the master cohort size to 10 times the cohort size (2159-63 619 subjects compared to 6196 subjects). Median agreement was 9.4% (interquartile range 15.3-16.2%). The teams' cohorts significantly differed from the master implementation by at least 2 baseline characteristics, and most of the teams differed by at least 5.

CONCLUSIONS

Independent research teams attempting to reproduce the study based on its free-text description alone produce different implementations that vary in the population size and composition. Sharing analytical code supported by a common data model and open-source tools allows reproducing a study unambiguously thereby preserving initial design choices.

Assessing medical product safety during pregnancy using parameterizable tools in the sentinel distributed database

PURPOSE

The US Food and Drug Administration established the Sentinel System to monitor the safety of medical products. A component of this system includes parameterizable analytic tools to identify mother-infant pairs and evaluate infant outcomes to enable the routine monitoring of the utilization and safety of drugs used in pregnancy. We assessed the feasibility of using the data and tools in the Sentinel System by assessing a known association between topiramate use during pregnancy and oral clefts in the infant.

METHODS

We identified mother-infant pairs using the mother-infant linkage table from six data partners contributing to the Sentinel Distributed Database from January 1, 2000, to September 30, 2015. We compared mother-infant pairs with first-trimester exposure to topiramate to mother-infant pairs that were topiramate-unexposed or lamotrigine-exposed and used a validated algorithm to identify oral clefts in the infant. We estimated adjusted risk ratios through propensity score stratification.

RESULTS

There were 2007 topiramate-exposed and 1 066 086 unexposed mother-infant pairs in the main comparison. In the active-comparator analysis, there were 1996 topiramate-exposed and 2859 lamotrigine-exposed mother-infant pairs. After propensity score stratification, the odds ratio for oral clefts was 2.92 (95% CI: 1.43, 5.93) comparing the topiramate-exposed to unexposed groups and 2.72 (95% CI: 0.75, 9.93) comparing the topiramate-exposed to lamotrigine-exposed groups.

CONCLUSIONS

We found an increased risk of oral clefts after topiramate exposure in the first trimester in the Sentinel database. These results are similar to prior published observational study results and demonstrate the ability of Sentinel's data and analytic tools to assess medical product safety in cohorts of mother-infant pairs in a timely manner.

Identification of pregnancies and their outcomes in healthcare claims data, 2008-2019: An algorithm

Pregnancy is a condition of broad interest across many medical and health services research domains, but one not easily identified in healthcare claims data. Our objective was to establish an algorithm to identify pregnant women and their pregnancies in claims data. We identified pregnancy-related diagnosis, procedure, and diagnosis-related group codes, accounting for the transition to International Statistical Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) diagnosis and procedure codes, in health encounter reporting on 10/1/2015. We selected women in Merative MarketScan commercial databases aged 15-49 years with pregnancy-related claims, and their infants, during 2008-2019. Pregnancies, pregnancy outcomes, and gestational ages were assigned using the constellation of service dates, code types, pregnancy outcomes, and linkage to infant records. We describe pregnancy outcomes and gestational ages, as well as maternal age, census region, and health plan type. In a sensitivity analysis, we compared our algorithm-assigned date of last menstrual period (LMP) to fertility procedure-based LMP (date of procedure + 14 days) among women with embryo transfer or insemination procedures. Among 5,812,699 identified pregnancies, most (77.9%) were livebirths, followed by spontaneous abortions (16.2%); 3,274,353 (72.2%) livebirths could be linked to infants. Most pregnancies were among women 25-34 years (59.1%), living in the South (39.1%) and Midwest (22.4%), with large employer-sponsored insurance (52.0%). Outcome distributions were similar across ICD-9 and ICD-10 eras, with some variation in gestational age distribution observed. Sensitivity analyses supported our algorithm's framework; algorithm- and fertility procedure-derived LMP estimates were within a week of each other (mean difference: -4 days [IQR: -13 to 6 days]; n = 107,870). We have developed an algorithm to identify pregnancies, their gestational age, and outcomes, across ICD-9 and ICD-10 eras using administrative data. This algorithm may be useful to reproductive health researchers investigating a broad range of pregnancy and infant outcomes.

Development and Validation of Algorithms to Estimate Live Birth Gestational Age in Medicaid Analytic eXtract Data

BACKGROUND

While healthcare utilization data are useful for postmarketing surveillance of drug safety in pregnancy, the start of pregnancy and gestational age at birth are often incompletely recorded or missing. Our objective was to develop and validate a claims-based live birth gestational age algorithm.

METHODS

Using the Medicaid Analytic eXtract (MAX) linked to birth certificates in three states, we developed four candidate algorithms based on: preterm codes; preterm or postterm codes; timing of prenatal care; and prediction models - using conventional regression and machine-learning approaches with a broad range of prespecified and empirically selected predictors. We assessed algorithm performance based on mean squared error (MSE) and proportion of pregnancies with estimated gestational age within 1 and 2 weeks of the gold standard, defined as the clinical or obstetric estimate of gestation on the birth certificate. We validated the best-performing algorithms against medical records in a nationwide sample. We quantified misclassification of select drug exposure scenarios due to estimated gestational age as positive predictive value (PPV), sensitivity, and specificity.

RESULTS

Among 114,117 eligible pregnancies, the random forest model with all predictors emerged as the best performing algorithm: MSE 1.5; 84.8% within 1 week and 96.3% within 2 weeks, with similar performance in the nationwide validation cohort. For all exposure scenarios, PPVs were >93.8%, sensitivities >94.3%, and specificities >99.4%.

CONCLUSIONS

We developed a highly accurate algorithm for estimating gestational age among live births in the nationwide MAX data, further supporting the value of these data for drug safety surveillance in pregnancy. See video abstract at, http://links.lww.com/EDE/B989 .

Changes in Medication Use During Pregnancy for Women with Chronic Conditions: An Analysis of Claims Data

PURPOSE

Evaluation of drug safety during pregnancy is dependent on the number of exposed women during routine clinical practice with data available for analysis. We examined medication fills in pregnant and nonpregnant women within select disease cohorts: general population, migraine, diabetes, and hyperlipidemia to explore the potential use of claims data to assess medication use and safety during pregnancy.

METHODS

This cohort study, using IBM MarketScan® Research Databases claims data, included women 10-54 years of age with pregnancy resulting in a liveborn infant between January 2010 and September 2015 and matched nonpregnant women. Medication use (antidepressants, antihypertensives, sedatives, glucose-lowering medications, antiepileptics, antipsychotics, lipid-lowering medications) was abstracted from pharmacy claims 180 days before last menstrual period through 180 days postdelivery.

RESULTS

Among 753,760 women in the general pregnancy population (including 73,268 migraine, 50,155 hyperlipidemia, and 8361 diabetes; non-exclusive cohorts), antidepressants, antihypertensives, and sedatives were the most commonly used medications during pregnancy. Medications of interest were less commonly used in the pregnancy cohort than in the matched nonpregnant cohort within each time period (e.g., 3.7% vs 13.1% antidepressant use in 1st trimester). Most prescription fills were less common during pregnancy then pre-pregnancy. Post-pregnancy, prescription fills increased to or exceeded pre-pregnancy levels, except antihypertensive and glucose-lowering medications, which increased during pregnancy.

CONCLUSIONS

Medication use among pregnant women was low and different from that among matched nonpregnant women. The underlying size of large commercial claims databases offer opportunities for efficient evaluation of potential safety concerns, particularly for rare drug exposures, compared to traditional pregnancy registries.

Patterns of antiemetic medication use during pregnancy: A multi-country retrospective cohort study

OBJECTIVE

To compare patterns in use of different antiemetics during pregnancy in Canada, the United Kingdom, and the United States, between 2002 and 2014.

METHODS

We constructed population-based cohorts of pregnant women using administrative healthcare data from five Canadian provinces (Alberta, British Columbia, Manitoba, Ontario, and Saskatchewan), the Clinical Practice Research Datalink from the United Kingdom, and the IBM MarketScan Research Databases from the United States. We included pregnancies ending in live births, stillbirth, spontaneous abortion, or induced abortion. We determined maternal use of antiemetics from pharmacy claims in Canada and the United States and from prescriptions in the United Kingdom.

RESULTS

The most common outcome of 3 848 734 included pregnancies (started 2002-2014) was live birth (66.7% of all pregnancies) followed by spontaneous abortion (20.2%). Use of antiemetics during pregnancy increased over time in all three countries. Canada had the highest prevalence of use of prescription antiemetics during pregnancy (17.7% of pregnancies overall, 13.2% of pregnancies in 2002, and 18.9% in 2014), followed by the United States (14.0% overall, 8.9% in 2007, and 18.1% in 2014), and the United Kingdom (5.0% overall, 4.2% in 2002, and 6.5% in 2014). Besides use of antiemetic drugs being considerably lower in the United Kingdom, the increase in its use over time was more modest. The most commonly used antiemetic was combination doxylamine/pyridoxine in Canada (95.2% of pregnancies treated with antiemetics), ondansetron in the United States (72.2%), and prochlorperazine in the United Kingdom (63.5%).

CONCLUSIONS

In this large cohort study, we observed an overall increase in antiemetic use during pregnancy, and patterns of use varied across jurisdictions. Continued monitoring of antiemetic use and further research are warranted to better understand the reasons for differences in use of these medications and to assess their benefit-risk profile in this population.

Temporal Events Detector for Pregnancy Care (TED-PC): A rule-based algorithm to infer gestational age and delivery date from electronic health records of pregnant women with and without COVID-19

OBJECTIVE

Identifying the time of SARS-CoV-2 viral infection relative to specific gestational weeks is critical for delineating the role of viral infection timing in adverse pregnancy outcomes. However, this task is difficult when it comes to Electronic Health Records (EHR). In combating the COVID-19 pandemic for maternal health, we sought to develop and validate a clinical information extraction algorithm to detect the time of clinical events relative to gestational weeks.

MATERIALS AND METHODS

We used EHR from the National COVID Cohort Collaborative (N3C), in which the EHR are normalized by the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). We performed EHR phenotyping, resulting in 270,897 pregnant women (June 1st, 2018 to May 31st, 2021). We developed a rule-based algorithm and performed a multi-level evaluation to test content validity and clinical validity, and extreme length of gestation (<150 or >300).

RESULTS

The algorithm identified 296,194 pregnancies (16,659 COVID-19, 174,744 without COVID-19) in 270,897 pregnant women. For inferring gestational age, 95% cases (n = 40) have moderate-high accuracy (Cohen's Kappa = 0.62); 100% cases (n = 40) have moderate-high granularity of temporal information (Cohen's Kappa = 1). For inferring delivery dates, the accuracy is 100% (Cohen's Kappa = 1). The accuracy of gestational age detection for the extreme length of gestation is 93.3% (Cohen's Kappa = 1). Mothers with COVID-19 showed higher prevalence in obesity or overweight (35.1% vs. 29.5%), diabetes (17.8% vs. 17.0%), chronic obstructive pulmonary disease (0.2% vs. 0.1%), respiratory distress syndrome or acute respiratory failure (1.8% vs. 0.2%).

DISCUSSION

We explored the characteristics of pregnant women by different gestational weeks of SARS-CoV-2 infection with our algorithm. TED-PC is the first to infer the exact gestational week linked with every clinical event from EHR and detect the timing of SARS-CoV-2 infection in pregnant women.

CONCLUSION

The algorithm shows excellent clinical validity in inferring gestational age and delivery dates, which supports multiple EHR cohorts on N3C studying the impact of COVID-19 on pregnancy.

Who is pregnant? defining real-world data-based pregnancy episodes in the National COVID Cohort Collaborative (N3C)

Objective

To define pregnancy episodes and estimate gestational aging within electronic health record (EHR) data from the National COVID Cohort Collaborative (N3C).

Materials and Methods

We developed a comprehensive approach, named H ierarchy and rule-based pregnancy episode I nference integrated with P regnancy P rogression S ignatures (HIPPS) and applied it to EHR data in the N3C from 1 January 2018 to 7 April 2022. HIPPS combines: 1) an extension of a previously published pregnancy episode algorithm, 2) a novel algorithm to detect gestational aging-specific signatures of a progressing pregnancy for further episode support, and 3) pregnancy start date inference. Clinicians performed validation of HIPPS on a subset of episodes. We then generated three types of pregnancy cohorts based on the level of precision for gestational aging and pregnancy outcomes for comparison of COVID-19 and other characteristics.

Results

We identified 628,165 pregnant persons with 816,471 pregnancy episodes, of which 52.3% were live births, 24.4% were other outcomes (stillbirth, ectopic pregnancy, spontaneous abortions), and 23.3% had unknown outcomes. We were able to estimate start dates within one week of precision for 431,173 (52.8%) episodes. 66,019 (8.1%) episodes had incident COVID-19 during pregnancy. Across varying COVID-19 cohorts, patient characteristics were generally similar though pregnancy outcomes differed.

Discussion

HIPPS provides support for pregnancy-related variables based on EHR data for researchers to define pregnancy cohorts. Our approach performed well based on clinician validation.

Conclusion

We have developed a novel and robust approach for inferring pregnancy episodes and gestational aging that addresses data inconsistency and missingness in EHR data.

Variation in guideline-based prenatal care in a commercially insured population

BACKGROUND

Despite the importance of prenatal care, quality measurement efforts have focused on the number of prenatal visits, or prenatal care adequacy, rather than the services received. It is unknown whether attending more prenatal visits is associated with receiving more guideline-based prenatal care services. The relationship between guideline-based prenatal care and patients' clinical and sociodemographic characteristics has also not been studied.

OBJECTIVE

This study aimed to measure the receipt of guideline-based prenatal care among pregnant patients and to describe the association between guideline-based prenatal care and the number of prenatal visits and other patient characteristics.

STUDY DESIGN

This was a retrospective descriptive cohort study of 176,092 pregnancy episodes between 2016 and 2019. We used de-identified administrative claims data on commercial enrollees across the United States from the OptumLabs Data Warehouse. We identified the following 8 components of prenatal care that are universally recommended by the American College of Obstetricians and Gynecologists and other guideline-issuing organizations: testing for sexually transmitted infections, obstetric laboratory test panel, urine culture, urinalysis, anatomy scan ultrasound, oral glucose tolerance test, tetanus, diphtheria, and pertussis vaccine, and group B Streptococcus test. We measured the proportion of pregnant patients who received each of these guideline-based services at the appropriate gestational age. We measured the association between guideline-based services and the number of prenatal visits and prenatal care adequacy. We described variation of guideline-based care according to patient age, comorbidities, high deductible health plan enrollment, and their county's rurality, health professional shortage area status, racial composition, median income, and educational attainment.

RESULTS

The 176,092 pregnancy episodes were mostly among patients aged 25 to 34 years (63%) with few pregnancy comorbidities (81%) and living in urban areas (92%). Guideline-based care varied by service, from 51% receiving a timely urinalysis to 90% receiving an anatomy scan and 91% completing testing for sexually transmitted infections. Patients with at least 4 prenatal visits received, on average, 6 of the 8 guideline-based services. Guideline-based care did not increase with additional prenatal visits and varied by patient characteristics. Rates of tetanus, diphtheria, and pertussis vaccination were lower in counties with high proportions of minoritized populations, lower education, and lower income.

CONCLUSION

In this commercially insured population, receipt of guideline-based care was not universal, did not increase with the number of prenatal visits, and varied by patient- and area-level characteristics. Measuring guideline-based care is feasible and may capture quality of prenatal care better than visit count or adequacy alone.

Birth without intervention in women with severe mental illness: cohort study

SUMMARY

The rate of normal birth outcomes (i.e. full-term births without intervention) for women with severe mental illness (SMI - psychotic and bipolar disorders) is not known. We examined rates of birth without intervention (spontaneous labour onset, spontaneous vaginal delivery without instruments, no episiotomy and no indication of pre- or post-delivery anaesthesia) in women with SMI (584 pregnancies) compared with a control population (70 942 pregnancies). Outcome ratios were calculated standardising for age. Women with SMI were less likely to have a birth without intervention (29.5%) relative to the control population (36.8%) (standardised outcome ratio 0.74, 95% CI 0.63-0.87).

Utility of fertility procedures and prenatal tests to estimate gestational age for live-births and stillbirths in electronic health plan databases

PURPOSE

Current algorithms to evaluate gestational age (GA) during pregnancy rely on hospital coding at delivery and are not applicable to non-live births. We developed an algorithm using fertility procedures and fertility tests, without relying on delivery coding, to develop a novel GA algorithm in live-births and stillbirths.

METHODS

Three pregnancy cohorts were identified from 16 health-plans in the Sentinel System: 1) hospital admissions for live-birth, 2) hospital admissions for stillbirth, and 3) medical chart-confirmed stillbirths. Fertility procedures and prenatal tests, recommended within specific GA windows were evaluated for inclusion in our GA algorithm. Our GA algorithm was developed against a validated delivery-based GA algorithm in live-births, implemented within a sample of chart-confirmed stillbirths, and compared to national estimates of GA at stillbirth.

RESULTS

Our algorithm, including fertility procedures and 11 prenatal tests, assigned a GA at delivery to 97.9% of live-births and 92.6% of stillbirths. For live-births (n = 4 701 207), it estimated GA within two weeks of a reference delivery-based GA algorithm in 82.5% of pregnancies, with a mean difference of 3.7 days. In chart-confirmed stillbirths (n = 49), it estimated GA within two weeks of the clinically recorded GA at delivery for 80% of pregnancies, with a mean difference of 11.1 days. Implementation of the algorithm in a cohort of stillbirths (n = 40 484) had an increased percentage of deliveries after 36 weeks compared to national estimates.

CONCLUSIONS

In a population of primarily commercially-insured pregnant women, fertility procedures and prenatal tests can estimate GA with sufficient sensitivity and accuracy for utility in pregnancy studies.

Emulating a target trial of the comparative effectiveness of clomiphene citrate and letrozole for ovulation induction

STUDY QUESTION

What are the comparative pregnancy outcomes in women who receive up to six consecutive cycles of ovulation induction with letrozole versus clomiphene citrate?

SUMMARY ANSWER

The risks of pregnancy, livebirth, multiple gestation, preterm birth, neonatal intensive care unit (NICU) admission and congenital malformations were higher for letrozole compared with clomiphene in participants with polycystic ovarian syndrome (PCOS), though no treatment differences were observed in those with unexplained infertility.

WHAT IS KNOWN ALREADY

Randomized trials have reported higher pregnancy and livebirth rates for letrozole versus clomiphene among individuals with PCOS, but no differences among those with unexplained infertility. None of these trials were designed to study maternal or neonatal complications.

STUDY DESIGN, SIZE, DURATION

We emulated a hypothetical trial of the comparative effectiveness of letrozole versus clomiphene citrate for ovulation induction among all women, then stratified by PCOS and unexplained infertility status. We used real-world data from a large healthcare claims database in the USA (2011-2015).

PARTICIPANTS/MATERIALS, SETTING, METHODS

We analyzed data from 18 120 women who initiated letrozole and 49 647 women who initiated clomiphene during 2011-2014, and who were aged 18-45 years with no history of diabetes, thyroid disease, liver disease or breast cancer and had no fertility treatments for 3 months before trial initiation. The treatment strategies were clomiphene citrate or letrozole for six consecutive cycles. The outcomes were pregnancy, livebirth, multiple gestation, preterm birth, small for gestational age (SGA), NICU admission and major congenital malformations. We estimated the probability of each outcome under each strategy via pooled logistic regression and used standardization to adjust for confounding and selection bias due to loss to follow-up.

MAIN RESULTS AND THE ROLE OF CHANCE

The estimated probabilities of pregnancy, livebirth and neonatal outcomes were similar under each strategy, both overall and among individuals with unexplained infertility. Among women with PCOS, the probability of pregnancy was 43% for letrozole vs 37% for clomiphene (risk difference [RD] = 6.0%; 95% CI: 4.4, 7.7) in the intention-to-treat analyses. The corresponding probability of livebirth was 32% vs 29% (RD = 3.1%; 95% CI: 1.5, 4.8). In per protocol analyses, the risk of multiple gestation was 19% vs 9%, the risk of preterm birth was 20% vs 15%, the risk of SGA was 5% vs 3%, the risk of NICU admission was 22% vs 16% and the risk of congenital malformation was 8% vs 2% among those with a livebirth.

LIMITATIONS, REASONS FOR CAUTION

We cannot completely rule out the possibility of residual confounding by body mass index or duration of infertility. However, we adjusted for proxies identified in administrative data and results did not change.

WIDER IMPLICATIONS OF THE FINDINGS

Our findings suggest that for women with unexplained infertility, the two treatments result in comparable probabilities of a livebirth. For women with PCOS, letrozole appears slightly more effective for attaining a livebirth. Neonatal outcomes were similar for the two treatments among women with unexplained infertility; we did not confirm the hypothesized higher risk of adverse neonatal outcomes for clomiphene versus letrozole. The risks of adverse neonatal outcomes were slightly greater among women with PCOS who were treated with letrozole versus clomiphene. It is likely that these effects are partially mediated through an increased risk of multiple gestation among women who received letrozole.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by the National Institute of Child Health and Human Development (R01HD088393). Y.-H.C. reports grants from the American Heart Association (834106) and NIH (R01HD097778). P.R. reports grants from the National Institutes of Health. J.H. reports grants from the National Institutes of Health, the Agency for Healthcare Research and Quality, and the California Health Care Foundation during the conduct of the study; and consulting for several health care delivery organizations including Cambridge Health Alliance, Columbia University, University of Southern California, Community Servings, and the Delta Health Alliance. S.H.-D. reports grants from the National Institutes of Health and the US Food and Drug Administration during the conduct of the study; grants to her institution from Takeda outside the submitted work; consulting for UCB (biopharmaceutical company) and Roche; and being an adviser for the Antipsychotics Pregnancy Registry and epidemiologist for the North American Antiepileptics Pregnancy Registry, both at Massachusetts General Hospital. M.A.H. reports grants from the National Institutes of Health and the U.S. Veterans Administration during the conduct of the study; being a consultant for Cytel; and being an adviser for ProPublica.

TRIAL REGISTRATION NUMBER

N/A.

OUP accepted manuscript

Background

Respiratory syncytial virus (RSV) is a leading cause of infant hospitalization in the United States. Preterm infants and those with select comorbidities are at highest risk of RSV-related complications. However, morbidity due to RSV infection is not confined to high-risk infants. We estimated the burden of medically attended (MA) RSV-associated lower respiratory tract infection (LRTI) among infants in the United States.

Methods

We analyzed commercial (MarketScan Commercial [MSC], Optum Clinformatics [OC]), and Medicaid (MarketScan Medicaid [MSM]) insurance claims data for infants born between April 2016 and February 2020. Using both specific and sensitive definitions of MA RSV LRTI, we estimated the burden of MA RSV LRTI during infants’ first RSV season, stratified by gestational age, comorbidity status, and highest level of medical care associated with the MA RSV LRTI diagnosis.

Results

According to the specific definition 75.0% (MSC), 78.6% (MSM), and 79.6% (OC) of MA RSV LRTI events during infants’ first RSV season occurred among term infants without known comorbidities.

Conclusions

Term infants without known comorbidities account for up to 80% of the MA RSV LRTI burden in the United States during infants’ first RSV season. Future prevention efforts should consider all infants.

Development and evaluation of standardized pregnancy identification and trimester distribution algorithms in U.S. IBM MarketScan® Commercial and Medicaid data

OBJECTIVES

Creation of new algorithms to identify pregnancies in automated health care claims databases is of public health importance, as it allows us to learn more about medication use and safety in a vulnerable population. Previous algorithms were largely created using international classification of disease codes, but despite the U.S. code transition in 2015, few algorithms are available with the latest ICD-10-CM codes.

METHODS

Using U.S. IBM MarketScan® Commercial Claims and Encounters and Multi-State Medicaid databases for women aged 10-64 years during 2014 and 2016, two pregnancy algorithms (ICD-9-CM and ICD-10-CM) were created using expert clinical review. The algorithms were evaluated by assessing the distribution of pregnancy outcomes (live birth and pregnancy losses) within each time-based cohort and the ability of the algorithms to identify select medication use during pregnancy. Medication exposure, demographics, comorbidities, and pregnancy outcomes were compared to published literature estimates for the two time periods.

RESULTS

For the IBM MarketScan® Commercial database, the algorithms identified 687,228 pregnancies in 2014 and 444,293 in 2016. In the IBM MarketScan® Medicaid database, 389,132 pregnancies in 2014 and 406,418 in 2016 were identified. Percentages of most pregnancy outcomes identified using the algorithms were similar to national data sources; however, percentages of preterm births and pregnancy losses were not comparable. Most medication use estimates from the algorithms were similar to or higher than published estimates.

CONCLUSIONS

By incorporating the latest ICD-10-CM codes, the new algorithms provide more complete estimates of medication use during pregnancy than algorithms using the outdated codes.

Prescription medication use and baseline health status of women with live-birth deliveries in a national data network

BACKGROUND

The US Food and Drug Administration increasingly uses administrative databases to conduct surveillance of medications used during pregnancy. To assess adverse fetal effects, administrative records must be linked between the mother and infant. The Sentinel Initiative's Mother-Infant Linkage Table provides a large cohort of linked deliveries from national, regional, and public insurance claims in the United States for the US Food and Drug Administration to conduct surveillance.

OBJECTIVE

This study aimed to describe baseline health conditions and prescription medication use during pregnancy in cohorts of women with a live-birth delivery linked and not linked to an infant.

STUDY DESIGN

Live-birth deliveries in women aged 10 to 54 years with at least 391 days of medical and drug coverage before delivery were identified in the Sentinel Mother-Infant Linkage Table from 2000 to 2019. Two cohorts were created for analysis: deliveries linked to infant records (linked deliveries, n=2,320,805) and deliveries unable to be linked to an infant (not-linked deliveries, n=504,785). Baseline health conditions, pregnancy history, healthcare utilization, and pregnancy conditions were defined using International Classification of Diseases, Ninth Revision, and International Classification of Diseases, Tenth Revision, diagnosis and procedure codes. Medication exposure was identified in a 90-day prepregnancy period and in each trimester.

RESULTS

Few notable differences were observed between the linked and not-linked deliveries except for maternal age and preterm birth; the not-linked cohort was 3.4 years younger on average and more likely to have a preterm delivery. At baseline among the linked deliveries, the most common conditions were depression and anxiety (5.2% each), acquired hypothyroidism (5.0%), pain conditions (3.9%), and asthma (2.8%). Among linked deliveries, 6.9% had evidence of gestational diabetes mellitus, 3.9% had gestational hypertension, and 4.5% had preeclampsia or eclampsia. The most commonly used medications during pregnancy in the linked deliveries were antibacterials (41.6%) and antiemetics (21.5%); similar medication use patterns were observed in the not-linked cohort. Age trends were observed for some medication groups; anti-infectives, pain medications, and antiemetics were more common in younger mothers, whereas endocrine medications were more common in older mothers.

CONCLUSION

Similarities between the linked and not-linked cohorts suggested that the ability to link mother and infant records is not influenced by maternal health status. In the linked cohort, the prevalence of specific pregnancy complications and medication use were similar to previously reported national estimates. Some baseline comorbidities, such as obesity and smoking, may be underestimated in the Sentinel Mother-Infant Linkage.

Validating Claims-Based Algorithms Determining Pregnancy Outcomes and Gestational Age Using a Linked Claims-Electronic Medical Record Database

Introduction

Pregnancy outcome identification and precise estimates of gestational age (GA) are critical in drug safety studies of pregnant women. Validated pregnancy outcome algorithms based on the International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS) have not previously been published.

Methods

We developed algorithms to classify pregnancy outcomes and estimate GA using ICD-10-CM/PCS and service codes on claims in the 2016–2018 IBM^® MarketScan^® Explorys^® Claims-EMR Data Set and compared the results with ob-gyn adjudication of electronic medical records (EMRs). Obstetric services were grouped into episodes using hierarchical and spacing requirements. GA was based on evidence with the highest clinical accuracy. Among pregnancies with obstetric EMRs, 100 full-term live births (FTBs), 100 preterm live births (PTBs), 100 spontaneous abortions (SAs), and 24 stillbirths were selected for review. Physicians adjudicated cases using Global Alignment of Immunization safety Assessment in pregnancy (GAIA) definitions applied to structured EMRs.

Results

The claims-based algorithms identified 34,204 pregnancies, of which 9.9% had obstetric EMRs. Of sampled pregnancies, 92 FTBs, 93 PTBs, 75 SAs, and 24 stillbirths were adjudicated. Among these pregnancies, the percent agreement was 97.8%, 62.4%, 100.0%, and 70.8% for FTBs, PTBs, SAs, and stillbirths, respectively. The percent agreement on GA within 7 and 28 days, respectively, was 85.9% and 100.0% for FTBs, 81.7% and 98.9% for PTBs, 61.3% and 94.7% for SAs, and 66.7% and 79.2% for stillbirths.

Conclusions

The pregnancy outcome algorithms had high agreement with physician adjudication of EMRs and may inform post-market maternal safety surveillance.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40264-021-01113-8.

Pregnant Mothers' Medical Claims and Associated Risk of Their Children being Diagnosed with Autism Spectrum Disorder

A retrospective analysis of administrative claims containing a diverse mixture of ages, ethnicities, and geographical regions across the United States was conducted in order to identify medical events that occur during pregnancy and are associated with autism spectrum disorder (ASD). The dataset used in this study is comprised of 123,824 pregnancies of which 1265 resulted in the child being diagnosed with ASD during the first five years of life. Logistic regression analysis revealed significant relationships between several maternal medical claims, made during her pregnancy and segmented by trimester, and the child's diagnosis of ASD. Having a biological sibling with ASD, maternal use of antidepressant medication and psychiatry services as well as non-pregnancy related claims such hospital visits, surgical procedures, and radiology exposure were related to an increased risk of ASD regardless of trimester. Urinary tract infections during the first trimester and preterm delivery during the second trimester were also related to an increased risk of ASD. Preventative and obstetrical care were associated with a decreased risk for ASD. A better understanding of the medical factors that increase the risk of having a child with ASD can lead to strategies to decrease risk or identify those children who require increased surveillance for the development of ASD to promote early diagnosis and intervention.

Birth and death notification via mobile devices: a mixed methods systematic review

BACKGROUND

Ministries of health, donors, and other decision-makers are exploring how they can use mobile technologies to acquire accurate and timely statistics on births and deaths. These stakeholders have called for evidence-based guidance on this topic. This review was carried out to support World Health Organization (WHO) recommendations on digital interventions for health system strengthening.

OBJECTIVES

Primary objective: To assess the effects of birth notification and death notification via a mobile device, compared to standard practice. Secondary objectives: To describe the range of strategies used to implement birth and death notification via mobile devices and identify factors influencing the implementation of birth and death notification via mobile devices.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, the Global Health Library, and POPLINE (August 2, 2019). We searched two trial registries (August 2, 2019). We also searched Epistemonikos for related systematic reviews and potentially eligible primary studies (August 27, 2019). We conducted a grey literature search using mHealthevidence.org (August 15, 2017) and issued a call for papers through popular digital health communities of practice. Finally, we conducted citation searches of included studies in Web of Science and Google Scholar (May 15, 2020). We searched for studies published after 2000 in any language.  SELECTION CRITERIA: For the primary objective, we included individual and cluster-randomised trials; cross-over and stepped-wedge study designs; controlled before-after studies, provided they have at least two intervention sites and two control sites; and interrupted time series studies. For the secondary objectives, we included any study design, either quantitative, qualitative, or descriptive, that aimed to describe current strategies for birth and death notification via mobile devices; or to explore factors that influence the implementation of these strategies, including studies of acceptability or feasibility. For the primary objective, we included studies that compared birth and death notification via mobile devices with standard practice. For the secondary objectives, we included studies of birth and death notification via mobile device as long as we could extract data relevant to our secondary objectives. We included studies of all cadres of healthcare providers, including lay health workers; administrative, managerial, and supervisory staff; focal individuals at the village or community level; children whose births were being notified and their parents/caregivers; and individuals whose deaths were being notified and their relatives/caregivers.

DATA COLLECTION AND ANALYSIS

For the primary objective, two authors independently screened all records, extracted data from the included studies and assessed risk of bias. For the analyses of the primary objective, we reported means and proportions, where appropriate. We used the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach to assess the certainty of the evidence and we prepared a 'Summary of Findings' table. For the secondary objectives, two authors screened all records, one author extracted data from the included studies and assessed methodological limitations using the WEIRD tool and a second author checked the data and assessments. We carried out a framework analysis using the Supporting the Use of Research Evidence (SURE) framework to identify themes in the data. We used the GRADE-CERQual (Confidence in the Evidence from Reviews of Qualitative research) approach to assess our confidence in the evidence and we prepared a 'Summary of Qualitative Findings' table.

MAIN RESULTS

For the primary objective, we included one study, which used a controlled before-after study design. The study was conducted in Lao People's Democratic Republic and assessed the effect of using mobile devices for birth notification on outcomes related to coverage and timeliness of Hepatitis B vaccination. However, we are uncertain of the effect of this approach on these outcomes because the certainty of this evidence was assessed as very low. The included study did not assess resource use or unintended consequences. For the primary objective, we did not identify any studies using mobile devices for death notification. For the secondary objective, we included 21 studies. All studies were conducted in low- or middle-income settings. They focussed on identification of births and deaths in rural, remote, or marginalised populations who are typically under-represented in civil registration processes or traditionally seen as having poor access to health services. The review identified several factors that could influence the implementation of birth-death notification via mobile device. These factors were tied to the health system, the person responsible for notifying, the community and families; and include: - Geographic barriers that could prevent people's access to birth-death notification and post-notification services - Access to health workers and other notifiers with enough training, supervision, support, and incentives - Monitoring systems that ensure the quality and timeliness of the birth and death data - Legal frameworks that allow births and deaths to be notified by mobile device and by different types of notifiers - Community awareness of the need to register births and deaths - Socio-cultural norms around birth and death - Government commitment - Cost to the system, to health workers and to families - Access to electricity and network connectivity, and compatibility with existing systems - Systems that protect data confidentiality We have low to moderate confidence in these findings. This was mainly because of concerns about methodological limitations and data adequacy.

AUTHORS' CONCLUSIONS

We need more, well-designed studies of the effect of birth and death notification via mobile devices and on factors that may influence its implementation.

Utilization of hydroxyprogesterone caproate among pregnancies with live birth deliveries in the sentinel distributed database

BACKGROUND

The U.S. Food and Drug Administration (FDA) approved Makena^® (hydroxyprogesterone caproate [HPC] injection) in February 2011 for reducing the risk of preterm birth (PTB) in women with a singleton pregnancy who had a history of singleton spontaneous PTB (sPTB). Makena was approved under accelerated approval and required a postmarketing study to verify its clinical benefits. However, the postmarketing trial (PROLONG) failed to verify Makena's clinical benefit to neonates and substantiate its effect on reducing the risk of recurrent PTB. This study examined the utilization of HPC, along with another progestogen (vaginal progesterone) used to reduce the risk of sPTB during pregnancy, to inform the landscape of HPC use in the United States.

METHODS

We included pregnant women aged 10-54 years with a live birth delivery from 1 January, 2008 to 31 December, 2018 in the Sentinel Distributed Database (SDD). We examined the prevalence of injectable HPC (Makena and its generics), compounded HPC, and vaginal progesterone use during the second and third trimesters during the study period. We also assessed the proportion of these HPC-exposed pregnancies with obstetrical conditions of interest as potential reasons for use: (1) history of preterm delivery; (2) cervical shortening in the current pregnancy; and (3) preterm labor in the current pregnancy.

RESULTS

We identified a total of 3,445,739 live-birth pregnancies (among 2.9 million women) between 2008 and 2018 in the SDD. Of these pregnancies, 6.5 per 1,000 pregnancies used injectable HPC, 2.3 per 1,000 pregnancies used compounded HPC, and 1.5 per 1,000 pregnancies used vaginal progesterone during the second and/or third trimesters. The yearly uptakeof pregnancies with injectable HPC use increased during the study period from 2.1 per 1,000 pregnancies in 2012 to 12.6 per 1,000 pregnancies in 2018; use of compounded HPC decreased from 3.3 per 1,000 pregnancies to 0.25 per 1,000 pregnancies over the same period. Of 16,524 pregnancies with injectable HPC use, 12,054 (73%) had at least one related obstetrical condition, including 6,439 (39%) with a recorded history of preterm delivery. In addition, 4,665 (28%) had a PTB recorded as the outcome for the current pregnancy.

CONCLUSIONS

We found modest use of HPC during the second and/or third trimesters among all live-birth pregnancies in SDD. The majority of pregnancies with injectable HPC use had at least one of three obstetrical indications of interest recorded before or during the pregnancy.

Selective serotonin reuptake inhibitor use patterns among commercially insured US pregnancies (2005-2014)

The goal of this study was to describe patterns of selective serotonin reuptake inhibitor (SSRI) use during pregnancy in a US cohort (2005-2014) of > 1 million commercially insured women using administrative claims. We used international classification of disease (ICD-9) diagnosis and procedure and current procedural terminology codes in the OptumLabs® Data Warehouse to identify deliveries (including losses) among US women aged 15-45 (n = 1,061,023). SSRI dispensings that overlapped with the timing of pregnancy were identified using national drug codes in linked pharmacy claims. Demographic characteristics were imputed based on residential location, census data, and consumer information. We investigated patterns by trimester, agent, and demographic subgroups. A total of 46,087 of women (4.34%) were dispensed SSRIs during the estimated pregnancy period. Sertraline was the most common overall and had the highest initial use after trimester 1, including women who switched from another SSRI, although dispensing for > 1 SSRI during pregnancy was uncommon. Use of vilazodone was rare and had the highest discontinuation after trimester 1, followed by paroxetine. SSRI use was more common among women who were older, White, college-educated, higher income (≥ $100,000), or resided in the Midwest. Paroxetine and dispensings for > 1 SSRI were more common in lower education subgroups. White women had the highest proportion of use in all trimesters of pregnancy, whereas Hispanic women had the lowest. Among commercially insured US women, SSRI use during pregnancy differed by agent and demographics. More research is needed to understand whether these differences are due to symptom reporting, cultural beliefs, and/or physician preferences.

Economic-Burden Trajectories in Commercially Insured US Infants With Respiratory Syncytial Virus Infection

BACKGROUND

This study evaluates the long-term respiratory syncytial virus (RSV) burden among preterm and full-term infants in the United States.

METHODS

Infants with birth hospitalization claims and ≥24 months of continuous enrollment were retrospectively identified in the Truven MarketScan Commercial Claims and Encounters database for the period 1 January 2004-30 September 2015. Infants with RSV infection in the first year of life (n = 38 473) were matched to controls (n = 76 825), and remaining imbalances in the number of individuals in each group were adjusted using propensity score methods. All-cause, respiratory-related, and asthma/wheezing-related 5-year average cumulative costs were measured.

RESULTS

Early premature (n = 213), premature (n = 397), late premature (n = 4446), and full-term (n = 33 417) RSV-infected infants were matched to 424, 791, 8875, and 66 735 controls, respectively. After 2 years since RSV diagnosis, all-cause cumulative costs for RSV-infected infants as compared to those for controls increased by $22 081 (95% confidence interval [CI], -$5800-$42 543) for early premature infants, by $14 034 (95% CI, $5095- $22 973) for premature infants, by $10 164 (95% CI, $8835-$11 493) for late premature infants, and by $5404 (95% CI, $5110-$5698) for full-term infants. The 5-year RSV burden increased to $39 490 (95% CI, $18 217-$60 764), $23 160 (95% CI, $13 002-$33 317),$13 755 (95% CI, $12 097-$15 414), and $6631 (95% CI, $6060-$7202), respectively. The RSV burden was higher when stratified by inpatient and outpatient setting and respiratory-related and asthma/wheezing-related costs.

CONCLUSIONS

The RSV burden extends across cost domains and prematurity, with the greatest burden incurred by the second year of follow-up. Findings are useful in determining the cost-effectiveness of RSV therapies in development.

Long-term Assessment of Healthcare Utilization 5 Years After Respiratory Syncytial Virus Infection in US Infants

BACKGROUND

Respiratory syncytial virus (RSV) is the primary cause of respiratory tract infections in infants; however, current burden estimates report only the short-term effects of acute infection.

METHODS

Infants with RSV infection and ≥24 months of continuous enrollment were retrospectively identified from the Truven MarketScan database (1 January 2004-30 September 2015). Exposed infants (n = 38 473) were propensity score matched to nonexposed controls (n = 76 825) by baseline characteristics and gestational age. Five-year cumulative all-cause, asthma/wheezing, and respiratory event-related hospitalization rates and physician and emergency department healthcare-resource utilization rates were assessed.

RESULTS

During follow-up, RSV-infected cohorts had higher average all-cause cumulative hospitalization rates, compared with controls, with values of 79.9 hospitalizations/100 patient-years (95% confidence interval [CI], 41.7-118.2) for 213 early premature infants (P < .001), 18.2 hospitalizations/100 patient-years (95% CI, .8-35.7) for 397 premature infants (P = .04), 34.2 hospitalizations/100 patient-years (95% CI, 29.1-39.2) for 4446 late premature infants (P < .001), and 16.1 hospitalizations/100 patient-years (95% CI, 14.9-17.4) for 33 417 full-term infants (P < .001). Cumulative rates of physician and emergency department visits were also higher for RSV-infected infants. Asthma/wheezing accounted for 10%-18% of total 5-year physician visits.

CONCLUSIONS

Infant RSV infection has a significant long-term healthcare-resource utilization impact across gestational ages for at least 5 years after infection, most of it in the first 2 years. Systematically collecting healthcare-resource utilization data will be important for cost-effectiveness evaluations of RSV interventions in planned or ongoing trials.

Development and evaluation of MADDIE: Method to Acquire Delivery Date Information from Electronic health records

OBJECTIVE

To develop an algorithm that infers patient delivery dates (PDDs) and delivery-specific details from Electronic Health Records (EHRs) with high accuracy; enabling pregnancy-level outcome studies in women's health.

MATERIALS AND METHODS

We obtained EHR data from 1,060,100 female patients treated at Penn Medicine hospitals or outpatient clinics between 2010-2017. We developed an algorithm called MADDIE: Method to Acquire Delivery Date Information from Electronic Health Records that infers a PDD for distinct deliveries based on EHR encounter dates assigned a delivery code, the frequency of code usage, and the time differential between code assignments. We validated MADDIE's PDDs against a birth log independently maintained by the Department of Obstetrics and Gynecology.

RESULTS

MADDIE identified 50,560 patients having 63,334 distinct deliveries. MADDIE was 98.6 % accurate (F₁-score 92.1 %) when compared to the birth log. The PDD was on average 0.68 days earlier than the true delivery date for patients with only one delivery (± 1.43 days) and 0.52 days earlier for patients with more than one delivery episode (± 1.11 days).

DISCUSSION

MADDIE is the first algorithm to successfully infer PDD information using only structured delivery codes and identify multiple deliveries per patient. MADDIE is also the first to validate the accuracy of the PDD using an external gold standard of known delivery dates as opposed to manual chart review of a sample.

CONCLUSION

MADDIE augments the EHR with delivery-specific details extracted with high accuracy and relies only on structured EHR elements while harnessing temporal information and the frequency of code usage to identify accurate PDDs.

Impact of the Transition from ICD-9-CM to ICD-10-CM on the Identification of Pregnancy Episodes in US Health Insurance Claims Data

Background

Before October 2015, pregnancy cohorts assembled from US health insurance claims have relied on medical encounters with International Classification of Diseases-ninth revision-clinical modification (ICD-9-CM) codes. We aimed to extend existing pregnancy identification algorithms into the ICD-10-CM era and evaluate performance.

Methods

We used national private insurance claims data (2005-2018) to develop and test a pregnancy identification algorithm. We considered validated ICD-9-CM diagnosis and procedure codes that identify medical encounters for live birth, stillbirth, ectopic pregnancy, abortions, and prenatal screening to identify pregnancies. We then mapped these codes to the ICD-10-CM system using general equivalent mapping tools and reconciled outputs with literature and expert opinion. Both versions were applied to the respective coding period to identify pregnancies. We required 45 weeks of health plan enrollment from estimated conception to ensure the capture of all pregnancy endpoints.

Results

We identified 7,060,675 pregnancy episodes, of which 50.1% met insurance enrollment requirements. Live-born deliveries comprised the majority (76.5%) of episodes, followed by abortions (20.3%). The annual prevalence for all pregnancy types was stable across the ICD transition period except for postterm pregnancies, which increased from 0.5% to 3.4%. We observed that ICD codes indicating gestational age were available for 86.8% of live-born deliveries in the ICD-10 era compared to 23.5% in the ICD-9 era. Patterns of prenatal tests remained stable across the transition period.

Conclusion

Translation of existing ICD-9-CM pregnancy algorithms into ICD-10-CM codes provided reasonable consistency in identifying pregnancy episodes across the ICD transition period. New codes for gestational age can potentially improve the precision of conception estimates and minimize measurement biases.

Phosphodiesterase type 5 inhibitor use among pregnant and reproductive-age women in the United States

PURPOSE

To assess the prevalence and potential indications of PDE5 inhibitor use among pregnant and reproductive-age women in the United States.

METHODS

We identified women 15 to 50 years with a livebirth from January 2001 through March 2018 in Sentinel Database. We assessed the prevalence of PDE5 inhibitor use prior to and during pregnancy by trimester, identified potential on- and off-label indications using predefined diagnosis codes recorded within 90 days before the estimated last menstrual period through delivery. Separately, we used data from IQVIA's National Prescription Audit and Total Patient Tracker to estimate the dispensed prescriptions for PDE5 inhibitors and the number of patients with PDE5 inhibitor prescriptions.

RESULTS

We identified approximately 3.3 million pregnancies during 2001 to 2018, 96 of which had PDE5 inhibitor use during pregnancy. Prevalence of PDE5 inhibitor use was 2.61, 0.62, and 0.62 per 100, 000 live-born pregnancies during the first, second, or third trimesters, respectively. Among women exposed to a PDE5 inhibitor from 90 days before conception to the end of pregnancy, 25.0%, 31.1%, and 15.5% had a diagnosis code for fetal growth restriction, preeclampsia, and pulmonary arterial hypertension. In IQVIA data, an estimated 223, 000 prescriptions from July 2015 through June 2018 and 58, 000 women received prescriptions for PDE5 inhibitors in 2017, of whom approximately 15, 000 (26%) were aged 15 to 50 years.

CONCLUSION

We found a low prevalence of PDE5 inhibitor use in pregnant and reproductive-age women. Given the very low prevalence of use and the inconsistency of neonatal mortality data across STRIDER centers, the risk to public health is low at present.

Trends in Preterm Delivery among Singleton Gestations with Critical Congenital Heart Disease

OBJECTIVE

To examine state-wide population trends in preterm delivery of children with critical congenital heart disease (CHD) over an 18-year period. We hypothesized that, coincident with early advancements in prenatal diagnosis, preterm delivery initially increased compared with the general population, and more recently has decreased.

STUDY DESIGN

Data from the Texas Public Use Data File 1999-2016 was used to evaluate annual percent preterm delivery (<37 weeks) in critical CHD (diagnoses requiring intervention at <1 year of age). We first evaluated for pattern change over time using joinpoint segmented regression. Trends in preterm delivery were then compared with all Texas livebirths. We then compared trends examining sociodemographic covariates including race/ethnicity, sex, and neighborhood poverty levels.

RESULTS

Of 7146 births with critical CHD, 1339 (18.7%) were delivered preterm. The rate of preterm birth increased from 1999 to 2004 (a mean increase of 1.69% per year) then decreased between 2005 and 2016 (a mean decrease of -0.41% per year). This represented a faster increase and then a similar decrease to that noted in the general population. Although the greatest proportion of preterm births occurred in newborns of Hispanic ethnicity and non-Hispanic black race, newborns with higher neighborhood poverty level had the most rapidly increasing rate of preterm delivery in the first era, and only a plateau rather than decrease in the latter era.

CONCLUSIONS

Rates of preterm birth for newborns with critical CHD in Texas first were increasing rapidly, then have been decreasing since 2005.

Interrupted time series analysis to assess changes in prescription filling around conception and implications for exposure misclassification

PURPOSE

Medication exposures in pregnancy are often defined by one or more prescription fills. Harmful effects could be underestimated if rapid discontinuation of use after pregnancy recognition is common. We used conception, a critical biological period, as an intervention in a novel application of interrupted time series analysis (ITSA).

METHODS

Among 645 049 pregnancies from the Medical Birth Registry (2005-2015) linked to the Norwegian Prescription Database, we modeled the total number of prescription fills in the 12 weeks before and after estimated conception date with ITSA. We examined psychostimulants, antidepressants, antipsychotics, and antiepileptics (AEDs; separated by use for epilepsy or other indications). We used relative measures (%) to compare model coefficients. We also compared number of pregnancies defined as exposed when the earliest fill considered was 30 days before the last menstrual period (LMP -30 days), LMP, or estimated conception date (LMP +14 days).

RESULTS

We observed a sudden decline in prescription fills from 2 weeks after conception and decreasing fills thereafter for psychostimulants, antidepressants, AEDs for other indications, and antipsychotics excluding incident users. Fills for AEDs for epilepsy did not fall after conception. Only 77% of pregnancies with fills for psychostimulants from LMP and 58% with fills from LMP -30 days had fills from conception. Similar figures for AEDs for epilepsy were 99% and 96%.

CONCLUSIONS

This application shows that ITSA can help researchers understand rapid changes in patient behavior around conception that have consequences for exposure misclassification in pregnancy drug safety studies. ITSA results can help pharmacoepidemiologists guide study exposure definitions.

Maternal and fetal outcomes following exposure to duloxetine in pregnancy: cohort study

OBJECTIVE

To evaluate the risk of adverse maternal and infant outcomes following in utero exposure to duloxetine.

DESIGN

Cohort study nested in the Medicaid Analytic eXtract for 2004-13.

SETTING

Publicly insured pregnancies in the United States.

PARTICIPANTS

Pregnant women 18 to 55 years of age and their liveborn infants.

INTERVENTIONS

Duloxetine exposure during the etiologically relevant time window, compared with no exposure to duloxetine, exposure to selective serotonin reuptake inhibitors, exposure to venlafaxine, and exposure to duloxetine before but not during pregnancy.

MAIN OUTCOME MEASURES

Congenital malformations overall, cardiac malformations, preterm birth, small for gestational age infant, pre-eclampsia, and postpartum hemorrhage.

RESULTS

Cohort sizes ranged from 1.3 to 4.1 million, depending on the outcome. The number of women exposed to duloxetine varied by cohort and exposure contrast and was around 2500-3000 for early pregnancy exposure and 900-950 for late pregnancy exposure. The base risk per 1000 unexposed women was 36.6 (95% confidence interval 36.3 to 36.9) for congenital malformations overall, 13.7 (13.5 to 13.9) for cardiovascular malformations, 107.8 (107.3 to 108.3) for preterm birth, 20.4 (20.1 to 20.6) for small for gestational age infant, 33.6 (33.3 to 33.9) for pre-eclampsia, and 23.3 (23.1 to 23.4) for postpartum hemorrhage. After adjustment for measured potential confounding variables, all baseline characteristics were well balanced for all exposure contrasts. In propensity score adjusted analyses versus unexposed pregnancies, the relative risk was 1.11 (95% confidence interval 0.93 to 1.33) for congenital malformations overall and 1.29 (0.99 to 1.68) for cardiovascular malformations. For preterm birth, the relative risk was 1.01 (0.92 to 1.10) for early exposure and 1.19 (1.04 to 1.37) for late exposure. For small for gestational age infants the relative risks were 1.14 (0.92 to 1.41) and 1.20 (0.83 to 1.72) for early and late pregnancy exposure, respectively, and for pre-eclampsia they were 1.12 (0.96 to 1.31) and 1.04 (0.80 to 1.35). The relative risk for postpartum hemorrhage was 1.53 (1.08 to 2.18). Results from sensitivity analyses were generally consistent with the findings from the main analyses.

CONCLUSIONS

On the basis of the evidence available to date, duloxetine is unlikely to be a major teratogen but may be associated with an increased risk of postpartum hemorrhage and a small increased risk of cardiac malformations. While continuing to monitor the safety of duloxetine as data accumulate over time, these potential small increases in risk of relatively uncommon outcomes must be weighed against the benefits of treating depression and pain during pregnancy in a given patient.

TRIAL REGISTRATION

EUPAS 15946.

Perinatal Outcomes Associated with Maternal Asthma and Its Severity and Control During Pregnancy

BACKGROUND

Estimates of the effects of maternal asthma on pregnancy outcomes are inconsistent across studies, possibly because of differences in exposure definition.

OBJECTIVE

To evaluate the risk of adverse perinatal outcomes associated with maternal asthma diagnosis, severity, and control in a large, nationally representative cohort.

METHODS

This study was conducted within the IBM Health MarketScan Commercial Claims and Encounters Database (2011-2015) and the Medicaid Analytic eXtract database (2000-2014). Asthma was identified by diagnosis and treatment codes, severity was based on medications dispensed, and control was based on short-acting β-agonist dispensations and exacerbations. We estimated the relative risks (RRs) of stillbirth, spontaneous abortion, preterm birth, small for gestational age (SGA), neonatal intensive care unit (NICU) admission, and congenital malformations, comparing pregnancies with differing asthma disease status.

RESULTS

We identified 29,882 pregnancies complicated by asthma in the MarketScan database and 160,638 in the Medicaid Analytic eXtract database. We observed no consistent associations between asthma diagnosis, severity, or control, and stillbirth, abortions, or malformations. However, we observed increased risks of prematurity, SGA, and NICU admission among women with asthma compared with those without asthma. Compared with women with well-controlled asthma, women with poor control late in pregnancy had an increased risk of preterm birth (relative risk, 1.39; 95% CI, 1.32-1.46) and NICU admission (relative risk, 1.26; 95% CI, 1.17-1.35). More severe asthma was associated with SGA (relative risk, 1.18; 95% CI, 1.07-1.30).

CONCLUSIONS

We did not observe an increased risk of pregnancy losses or malformations among women with asthma. However, we found an association between asthma severity and SGA, and between exacerbations late in pregnancy and preterm delivery and NICU admission.

Medication Use During Pregnancy in Mainland China: A Cross-Sectional Analysis of a National Health Insurance Database

Purpose

This study aims to illustrate the prevalence and patterns of medication use among pregnant women in mainland China.

Patients and methods

Hospital and drugstore service data for a nationally representative sample of basic medical insurance (BMI) beneficiaries in 2015 were obtained from the China Health Insurance Association (CHIRA) database. A total of 7946 women who had singleton deliveries in 2015, aged between 12 and 54, and whose records in the CHIRA database covered at least one trimester were included in this study. We conducted descriptive analyses of sample characteristics, medication use prevalence, and number and types of medications used.

Results

We found that 11.7% of women used at least one medication during the course of pregnancy (median number of medications used = 6.7). Medication use was more common among those who were older, residing in Eastern China, or employed. Most commonly used medication groups by the Anatomical Therapeutic Chemical Classification System were B (Blood and blood forming organs, 49.3%), A (Alimentary tract and metabolism, 48.1%), G (Genito urinary system and sex hormones, 38.1%) and J (Antiinfectives for systemic use, 31.6%). Intravenous solutions, vitamins and minerals, progestogens, and beta-lactam antibacterials were the most frequently used medications from each of these four ATC groups, respectively. Moreover, 7.1% used at least one medication contraindicated in pregnancy.

Conclusion

This study showed that around one in 10 women used medication during pregnancy in mainland China and found possible cases of inappropriate or unsafe medication use.

Safety of medication use during pregnancy in mainland China: based on a national health insurance database in 2015

Background

Medication safety during pregnancy has drawn global attention, little of which has been reported about the Chinese population. This study aims to describe patterns and risks of medication use among pregnant women in mainland China with reference to the U.S. Food and Drug Administration (FDA) pregnancy risk category.

Methods

Hospital diagnostic and drug dispensing information of a national representative sample of basic medical insurance (BMI) beneficiaries was obtained from the China Health Insurance Association (CHIRA) database in 2015. Prevalence of use and number of medicines involved in each risk category were calculated. Most commonly used medicines from each risk category were illustrated. Factors associated with the use of category D/X medicines were evaluated through multiple logistic regression.

Results

Out of 11,373 women who had singleton deliveries in 2015, there were 2896 women with records covering their entire pregnancies, 5377, and 7946 women with records through the 2nd, and the 3rd trimester, respectively. It was found that 11.1% pregnant women used at least one medication and a total of 321 medications had been used during pregnancy. Most pregnant women used medicines which were classified FDA category C (66.2%), followed by category B (57.8%), category A (16.8%), category X (7.5%) and category D (5.0%). The most commonly used medicines from category D and X were anxiolytics and hormonal preparations respectively. Women who were from mid-western area (p = 0.045) or used four or more medications (p < 0.001) were more likely to use category D/X medicines.

Conclusions

This study revealed that about one in ten pregnant women used at least one medication during pregnancy in China and a significant number of them used FDA Category D or X medicines. The usage patterns identified in the present study indicate that sub-optimal medicine use might exist warranting further evaluation and intervention in future studies. More efforts are needed to uncover the safety concerns about medication use during pregnancy and improve current information system for clinical practice.

Use of Antidiabetic drugs during pregnancy among U.S. women with Livebirth deliveries in the Mini-Sentinel system

BACKGROUND

As the prevalence of diabetes mellitus increases in the population, the exposure to antidiabetic drugs (ADDs) during pregnancies is expected to grow, as has been seen over the last decade. The objective of this study was to estimate the prevalence of ADD use during pregnancy among women in the Mini-Sentinel Distributed Database (MSDD) who delivered a liveborn infant.

METHODS

We identified qualifying livebirth pregnancies among women aged 10 to 54 years in the MSDD from 2001 to 2013. ADD use was estimated using outpatient pharmacy dispensing claims and days-supplied among three cohorts: all livebirth pregnancies, pregnancies among women with pre-existing diabetes, and pregnancies among women without prior ADD use.

RESULTS

Among the 1.9 million pregnancies in the MSDD that resulted in a livebirth from 2001 to 2013, 4.4% were exposed to an ADD. Of the 15,606 pregnancies (0.8%) with pre-existing diabetes, 92.8% were also exposed during the pregnancy period. The most commonly used product in these pregnancies was insulin (75.6% of pregnancies). In contrast, in pregnancies of women without prior ADD use, the most commonly used products were glyburide and insulin, and most of these users were diagnosed with gestational diabetes.

CONCLUSIONS

Patterns of ADD use during pregnancy described here, along with changes in disease incidence and management, highlight the importance of continuing surveillance of ADD utilization patterns and examining the safety and effectiveness of these products in pregnancy.

Opioid Use During Pregnancy, Observations of Opioid Use, and Secular Trend From 2006 to 2014 at HealthPartners Medical Group

OBJECTIVES

To determine the prevalence of opioid use before, during, and after pregnancy and describe its use based on patient-specific characteristics. Determine secular trend of opioid use 2006 to 2014.

MATERIALS AND METHODS

Retrospective cohort study. A large Upper Midwest integrated health care system and insurer. Female individuals age 10 to 50 years with a delivery diagnosis from July 1, 2006 through June 30, 2014.

MAIN OUTCOME MEASURE

prevalence of opioid use before, during, and after pregnancy; description of opioid use during these time periods.

RESULTS

From 11,565 deliveries among 9690 unique women, 862 (7.5%) deliveries were associated with significant opioid use. Significant opioid use was associated with single marital status, Cesarean section, Medicaid coverage, tobacco use, depression, anxiety, bipolar disorder, substance use disorder, nonopioid analgesic use, and referral to physical therapy, psychotherapy, or pain specialists. From 2006 to 2014 opioid use decreased from 9% to 6% before, during, and after pregnancy with a rate of change per year of -0.2%.

DISCUSSION

Known risk factors including tobacco and alcohol use, mental health diagnoses, substance use disorder, or Medicaid enrollment may enable enhanced assessments and targeted interventions to reduce unnecessary prescribing and use of opioids among pregnant women and those who might become pregnant. Strategies to decrease opioid use during pregnancy should be considered by health care systems and health plans to reduce opioid prescribing in this patient population.

Data-driven queries between medications and spontaneous preterm birth among 2.5 million pregnancies

BACKGROUND

Our goal was to develop an approach that can systematically identify potential associations between medication prescribed in pregnancy and spontaneous preterm birth (sPTB) by mining large administrative "claims" databases containing hundreds of medications. One such association that we illustrate emerged with antiviral medications used for herpes treatment.

METHODS

IBM MarketScan® databases (2007-2016) were used. A pregnancy cohort was established using International Classification of Diseases (ICD-9/10) codes. Multiple hypothesis testing and the Benjamini-Hochberg procedure that limited false discovery rate at 5% revealed, among 863 medications, five that showed odds ratios (ORs) <1. The statistically strongest was an association between antivirals and sPTB that we illustrate as a real example of our approach, specifically for treatment of genital herpes (GH). Three groups of women were identified based on diagnosis of GH and treatment during the first 36 weeks of pregnancy: (a) GH without treatment; (b) GH treated with antivirals; (c) no GH or treatment.

RESULTS

We identified 2,538,255 deliveries. 0.98% women had a diagnosis of GH. Among them, 60.0% received antiviral treatment. Women with treated GH had OR < 1, (OR [95% CI] = 0.91 [0.85, 0.98]). In contrast, women with untreated GH had a small increased risk of sPTB (OR [95% CI] =1.22 [1.14, 1.32]).

CONCLUSIONS

Data-driven approaches can effectively generate new hypotheses on associations between medications and sPTB. This analysis led us to examine the association with GH treatment. While unknown confounders may impact these findings, our results indicate that women with untreated GH have a modest increased risk of sPTB.

Safety of acupuncture during pregnancy: a retrospective cohort study in Korea

OBJECTIVE

The present study aimed to analyse the Korean National Health Insurance Service (NHIS) cohort data to examine the safety of acupuncture therapy during pregnancy.

DESIGN

Retrospective cohort.

SETTING

Korea.

POPULATION OR SAMPLE

Women with confirmed pregnancy between 2003 and 2012 from the 2002-13 NHIS sample cohort (n = 20 799).

METHODS

Women with confirmed pregnancy were identified and divided into acupuncture or control group for comparison of their outcomes. Differences in other factors such as age, and rate of high-risk pregnancy and multiple pregnancy were examined. In the acupuncture group, the most frequent acupuncture diagnosis codes and the timing of treatment were also investigated.

MAIN OUTCOME MEASURES

Incidence of full-term delivery, preterm delivery and stillbirth by pregnancy duration and among the high-risk and multiple pregnancy groups.

RESULTS

Of 20 799 pregnant women analysed, 1030 (4.95%) and 19 749 were in the acupuncture and control groups, respectively. Both overall (odds ratio [OR] 1.23; 95% CI 0.98-1.54), and in the stratified analysis of high-risk pregnancies (OR 1.09; 95% CI 0.73-1.64), there was no significant difference between acupuncture and control groups in preterm deliveries. No stillbirths occurred in the acupuncture group and 0.035% of pregnancies resulted in stillbirths in the control group.

CONCLUSION

No significant difference in delivery outcomes (preterm delivery and stillbirth) was observed between confirmed pregnancies in the acupuncture and control groups. Therefore, in pregnancy, acupuncture therapy may be a safe therapeutic modality for relieving discomfort without an adverse delivery outcome.

TWEETABLE ABSTRACT

In pregnancy, acupuncture therapy may be a safe therapeutic modality for relieving discomfort without an adverse outcome.